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diff --git a/site/datasets/final/cofw.csv b/site/datasets/final/cofw.csv deleted file mode 100644 index 3b50c56d..00000000 --- a/site/datasets/final/cofw.csv +++ /dev/null @@ -1,233 +0,0 @@ -index,dataset_name,key,lat,lng,loc,loc_type,paper_id,paper_type,paper_url,title,year -0,COFW,cofw,0.0,0.0,,,2724ba85ec4a66de18da33925e537f3902f21249,main,http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6751298,Robust Face Landmark Estimation under Occlusion,2013 -1,COFW,cofw,23.04436505,113.36668458,Guangzhou University,edu,293d69d042fe9bc4fea256c61915978ddaf7cc92,citation,https://doi.org/10.1007/978-981-10-7302-1_6,Face Recognition by Coarse-to-Fine Landmark Regression with Application to ATM Surveillance,2017 -2,COFW,cofw,23.09461185,113.28788994,Sun Yat-Sen University,edu,293d69d042fe9bc4fea256c61915978ddaf7cc92,citation,https://doi.org/10.1007/978-981-10-7302-1_6,Face Recognition by Coarse-to-Fine Landmark Regression with Application to ATM Surveillance,2017 -3,COFW,cofw,32.87935255,-117.23110049,"University of California, San Diego",edu,d68dbb71b34dfe98dee0680198a23d3b53056394,citation,http://pdfs.semanticscholar.org/d68d/bb71b34dfe98dee0680198a23d3b53056394.pdf,VIVA Face-off Challenge: Dataset Creation and Balancing Privacy,2015 -4,COFW,cofw,40.0044795,116.370238,Chinese Academy of Sciences,edu,c2474202d56bb80663e7bece5924245978425fc1,citation,https://doi.org/10.1109/ICIP.2016.7532771,Localize heavily occluded human faces via deep segmentation,2016 -5,COFW,cofw,31.83907195,117.26420748,University of Science and Technology of China,edu,a7a3ec1128f920066c25cb86fbc33445ce613919,citation,https://doi.org/10.1109/VCIP.2017.8305115,Joint facial landmark detection and action estimation based on deep probabilistic random forest,2017 -6,COFW,cofw,42.9336278,-78.88394479,SUNY Buffalo,edu,a7a3ec1128f920066c25cb86fbc33445ce613919,citation,https://doi.org/10.1109/VCIP.2017.8305115,Joint facial landmark detection and action estimation based on deep probabilistic random forest,2017 -7,COFW,cofw,42.718568,-84.47791571,Michigan State University,edu,0141cb33c822e87e93b0c1bad0a09db49b3ad470,citation,http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7298876,Unconstrained 3D face reconstruction,2015 -8,COFW,cofw,22.2081469,114.25964115,University of Hong Kong,edu,fb87045600da73b07f0757f345a937b1c8097463,citation,https://pdfs.semanticscholar.org/5c54/2fef80a35a4f930e5c82040b52c58e96ce87.pdf,Reflective Regression of 2D-3D Face Shape Across Large Pose,2016 -9,COFW,cofw,1.2962018,103.77689944,National University of Singapore,edu,1fe59275142844ce3ade9e2aed900378dd025880,citation,http://www.cv-foundation.org/openaccess/content_iccv_2015_workshops/w25/papers/Xiao_Facial_Landmark_Detection_ICCV_2015_paper.pdf,Facial Landmark Detection via Progressive Initialization,2015 -10,COFW,cofw,42.7298459,-73.67950216,Rensselaer Polytechnic Institute,edu,171d8a39b9e3d21231004f7008397d5056ff23af,citation,http://arxiv.org/abs/1709.08130,"Simultaneous Facial Landmark Detection, Pose and Deformation Estimation Under Facial Occlusion",2017 -11,COFW,cofw,52.17638955,0.14308882,University of Cambridge,edu,4ae291b070ad7940b3c9d3cb10e8c05955c9e269,citation,http://www.cl.cam.ac.uk/~pr10/publications/icmi14.pdf,Automatic Detection of Naturalistic Hand-over-Face Gesture Descriptors,2014 -12,COFW,cofw,39.9041999,116.4073963,"360 AI Institute, Beijing, China",company,54f169ad7d1f6c9ce94381e9b5ccc1a07fd49cc6,citation,http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7911334,Towards Robust and Accurate Multi-View and Partially-Occluded Face Alignment,2018 -13,COFW,cofw,51.2352438,7.1593132,Delphi Deutschland GMBH,company,54f169ad7d1f6c9ce94381e9b5ccc1a07fd49cc6,citation,http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7911334,Towards Robust and Accurate Multi-View and Partially-Occluded Face Alignment,2018 -14,COFW,cofw,40.0044795,116.370238,Chinese Academy of Sciences,edu,54f169ad7d1f6c9ce94381e9b5ccc1a07fd49cc6,citation,http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7911334,Towards Robust and Accurate Multi-View and Partially-Occluded Face Alignment,2018 -15,COFW,cofw,40.0044795,116.370238,Chinese Academy of Sciences,edu,bc910ca355277359130da841a589a36446616262,citation,http://www.cv-foundation.org/openaccess/content_iccv_2015/papers/Huang_Conditional_High-Order_Boltzmann_ICCV_2015_paper.pdf,Conditional High-Order Boltzmann Machine: A Supervised Learning Model for Relation Learning,2015 -16,COFW,cofw,29.7207902,-95.34406271,University of Houston,edu,466f80b066215e85da63e6f30e276f1a9d7c843b,citation,http://doi.ieeecomputersociety.org/10.1109/FG.2017.81,Joint Head Pose Estimation and Face Alignment Framework Using Global and Local CNN Features,2017 -17,COFW,cofw,37.4102193,-122.05965487,Carnegie Mellon University,edu,3146fabd5631a7d1387327918b184103d06c2211,citation,http://www.cv-foundation.org/openaccess/content_cvpr_2016_workshops/w18/papers/Jeni_Person-Independent_3D_Gaze_CVPR_2016_paper.pdf,Person-Independent 3D Gaze Estimation Using Face Frontalization,2016 -18,COFW,cofw,40.44415295,-79.96243993,University of Pittsburgh,edu,3146fabd5631a7d1387327918b184103d06c2211,citation,http://www.cv-foundation.org/openaccess/content_cvpr_2016_workshops/w18/papers/Jeni_Person-Independent_3D_Gaze_CVPR_2016_paper.pdf,Person-Independent 3D Gaze Estimation Using Face Frontalization,2016 -19,COFW,cofw,42.718568,-84.47791571,Michigan State University,edu,b53485dbdd2dc5e4f3c7cff26bd8707964bb0503,citation,http://doi.org/10.1007/s11263-017-1012-z,Pose-Invariant Face Alignment via CNN-Based Dense 3D Model Fitting,2017 -20,COFW,cofw,38.83133325,-77.30798839,George Mason University,edu,a9426cb98c8aedf79ea19839643a7cf1e435aeaa,citation,https://doi.org/10.1109/GlobalSIP.2016.7905998,Cascaded regression for 3D pose estimation for mouse in fisheye lens distorted monocular images,2016 -21,COFW,cofw,39.00041165,-77.10327775,National Institutes of Health,edu,a9426cb98c8aedf79ea19839643a7cf1e435aeaa,citation,https://doi.org/10.1109/GlobalSIP.2016.7905998,Cascaded regression for 3D pose estimation for mouse in fisheye lens distorted monocular images,2016 -22,COFW,cofw,41.3861759,2.1248717,"Transmural Biotech, Barcelona, Spain",edu,a9426cb98c8aedf79ea19839643a7cf1e435aeaa,citation,https://doi.org/10.1109/GlobalSIP.2016.7905998,Cascaded regression for 3D pose estimation for mouse in fisheye lens distorted monocular images,2016 -23,COFW,cofw,26.88111275,112.62850666,Hunan University,edu,1fe1a78c941e03abe942498249c041b2703fd3d2,citation,http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8393355,Face alignment based on improved shape searching,2017 -24,COFW,cofw,32.8164178,130.72703969,Kumamoto University,edu,7aafeb9aab48fb2c34bed4b86755ac71e3f00338,citation,http://pdfs.semanticscholar.org/7aaf/eb9aab48fb2c34bed4b86755ac71e3f00338.pdf,Real Time 3D Facial Movement Tracking Using a Monocular Camera,2016 -25,COFW,cofw,31.28473925,121.49694909,Tongji University,edu,7aafeb9aab48fb2c34bed4b86755ac71e3f00338,citation,http://pdfs.semanticscholar.org/7aaf/eb9aab48fb2c34bed4b86755ac71e3f00338.pdf,Real Time 3D Facial Movement Tracking Using a Monocular Camera,2016 -26,COFW,cofw,32.8164178,130.72703969,Kumamoto University,edu,6fdf2f4f7ae589af6016305a17d460617d9ef345,citation,https://doi.org/10.1109/ICIP.2015.7350767,Robust facial landmark localization using multi partial features,2015 -27,COFW,cofw,31.28473925,121.49694909,Tongji University,edu,6fdf2f4f7ae589af6016305a17d460617d9ef345,citation,https://doi.org/10.1109/ICIP.2015.7350767,Robust facial landmark localization using multi partial features,2015 -28,COFW,cofw,31.21051105,29.91314562,Alexandria University,edu,9a4c45e5c6e4f616771a7325629d167a38508691,citation,http://www.cv-foundation.org/openaccess/content_cvpr_workshops_2015/W02/papers/Mostafa_A_Facial_Features_2015_CVPR_paper.pdf,A facial features detector integrating holistic facial information and part-based model,2015 -29,COFW,cofw,27.18794105,31.17009498,Assiut University,edu,9a4c45e5c6e4f616771a7325629d167a38508691,citation,http://www.cv-foundation.org/openaccess/content_cvpr_workshops_2015/W02/papers/Mostafa_A_Facial_Features_2015_CVPR_paper.pdf,A facial features detector integrating holistic facial information and part-based model,2015 -30,COFW,cofw,38.2167565,-85.75725023,University of Louisville,edu,9a4c45e5c6e4f616771a7325629d167a38508691,citation,http://www.cv-foundation.org/openaccess/content_cvpr_workshops_2015/W02/papers/Mostafa_A_Facial_Features_2015_CVPR_paper.pdf,A facial features detector integrating holistic facial information and part-based model,2015 -31,COFW,cofw,37.5901411,127.0362318,Korea University,edu,5957936195c10521dadc9b90ca9b159eb1fc4871,citation,https://doi.org/10.1109/TCE.2016.7838098,LBP-ferns-based feature extraction for robust facial recognition,2016 -32,COFW,cofw,33.5866784,-101.87539204,Electrical and Computer Engineering,edu,ebb3d5c70bedf2287f9b26ac0031004f8f617b97,citation,https://doi.org/10.1109/MSP.2017.2764116,"Deep Learning for Understanding Faces: Machines May Be Just as Good, or Better, than Humans",2018 -33,COFW,cofw,39.2899685,-76.62196103,University of Maryland,edu,ebb3d5c70bedf2287f9b26ac0031004f8f617b97,citation,https://doi.org/10.1109/MSP.2017.2764116,"Deep Learning for Understanding Faces: Machines May Be Just as Good, or Better, than Humans",2018 -34,COFW,cofw,40.0141905,-83.0309143,University of Electronic Science and Technology of China,edu,21a2f67b21905ff6e0afa762937427e92dc5aa0b,citation,http://pdfs.semanticscholar.org/21a2/f67b21905ff6e0afa762937427e92dc5aa0b.pdf,Extra Facial Landmark Localization via Global Shape Reconstruction,2017 -35,COFW,cofw,40.0141905,-83.0309143,University of Electronic Science and Technology of China,edu,88e2574af83db7281c2064e5194c7d5dfa649846,citation,http://pdfs.semanticscholar.org/88e2/574af83db7281c2064e5194c7d5dfa649846.pdf,A Robust Shape Reconstruction Method for Facial Feature Point Detection,2017 -36,COFW,cofw,29.7207902,-95.34406271,University of Houston,edu,607aebe7568407421e8ffc7b23a5fda52650ad93,citation,https://doi.org/10.1109/ISBA.2016.7477237,Face alignment via an ensemble of random ferns,2016 -37,COFW,cofw,-27.49741805,153.01316956,University of Queensland,edu,710c3aaffef29730ffd909a63798e9185f488327,citation,https://doi.org/10.1109/ICPR.2016.7900095,The GIST of aligning faces,2016 -38,COFW,cofw,32.7283683,-97.11201835,University of Texas at Arlington,edu,411dc8874fd7b3a9a4c1fd86bb5b583788027776,citation,https://pdfs.semanticscholar.org/701f/56f0eac9f88387de1f556acef78016b05d52.pdf,Direct Shape Regression Networks for End-to-End Face Alignment,2018 -39,COFW,cofw,34.1235825,108.83546,Xidian University,edu,411dc8874fd7b3a9a4c1fd86bb5b583788027776,citation,https://pdfs.semanticscholar.org/701f/56f0eac9f88387de1f556acef78016b05d52.pdf,Direct Shape Regression Networks for End-to-End Face Alignment,2018 -40,COFW,cofw,30.44235995,-84.29747867,Florida State University,edu,1ed6c7e02b4b3ef76f74dd04b2b6050faa6e2177,citation,http://pdfs.semanticscholar.org/6433/c412149382418ccd8aa966aa92973af41671.pdf,Face Detection with a 3D Model,2014 -41,COFW,cofw,39.00041165,-77.10327775,National Institutes of Health,edu,1ed6c7e02b4b3ef76f74dd04b2b6050faa6e2177,citation,http://pdfs.semanticscholar.org/6433/c412149382418ccd8aa966aa92973af41671.pdf,Face Detection with a 3D Model,2014 -42,COFW,cofw,32.87935255,-117.23110049,"University of California, San Diego",edu,43776d1bfa531e66d5e9826ff5529345b792def7,citation,http://cvrr.ucsd.edu/scmartin/presentation/DriveAnalysisByLookingIn-ITSC2015-NDS.pdf,Automatic Critical Event Extraction and Semantic Interpretation by Looking-Inside,2015 -43,COFW,cofw,38.99203005,-76.9461029,University of Maryland College Park,edu,f7824758800a7b1a386db5bd35f84c81454d017a,citation,https://arxiv.org/pdf/1702.05085.pdf,KEPLER: Keypoint and Pose Estimation of Unconstrained Faces by Learning Efficient H-CNN Regressors,2017 -44,COFW,cofw,38.99203005,-76.9461029,University of Maryland College Park,edu,ceeb67bf53ffab1395c36f1141b516f893bada27,citation,http://pdfs.semanticscholar.org/ceeb/67bf53ffab1395c36f1141b516f893bada27.pdf,Face Alignment by Local Deep Descriptor Regression,2016 -45,COFW,cofw,40.47913175,-74.43168868,Rutgers University,edu,ceeb67bf53ffab1395c36f1141b516f893bada27,citation,http://pdfs.semanticscholar.org/ceeb/67bf53ffab1395c36f1141b516f893bada27.pdf,Face Alignment by Local Deep Descriptor Regression,2016 -46,COFW,cofw,39.2899685,-76.62196103,University of Maryland,edu,ceeb67bf53ffab1395c36f1141b516f893bada27,citation,http://pdfs.semanticscholar.org/ceeb/67bf53ffab1395c36f1141b516f893bada27.pdf,Face Alignment by Local Deep Descriptor Regression,2016 -47,COFW,cofw,1.2962018,103.77689944,National University of Singapore,edu,3be8f1f7501978287af8d7ebfac5963216698249,citation,https://pdfs.semanticscholar.org/3be8/f1f7501978287af8d7ebfac5963216698249.pdf,Deep Cascaded Regression for Face Alignment,2015 -48,COFW,cofw,23.09461185,113.28788994,Sun Yat-Sen University,edu,3be8f1f7501978287af8d7ebfac5963216698249,citation,https://pdfs.semanticscholar.org/3be8/f1f7501978287af8d7ebfac5963216698249.pdf,Deep Cascaded Regression for Face Alignment,2015 -49,COFW,cofw,51.7534538,-1.25400997,University of Oxford,edu,a3d0ebb50d49116289fb176d28ea98a92badada6,citation,https://pdfs.semanticscholar.org/a3d0/ebb50d49116289fb176d28ea98a92badada6.pdf,Unsupervised Learning of Object Landmarks through Conditional Image Generation,2018 -50,COFW,cofw,55.94951105,-3.19534913,University of Edinburgh,edu,a3d0ebb50d49116289fb176d28ea98a92badada6,citation,https://pdfs.semanticscholar.org/a3d0/ebb50d49116289fb176d28ea98a92badada6.pdf,Unsupervised Learning of Object Landmarks through Conditional Image Generation,2018 -51,COFW,cofw,30.642769,104.06751175,"Sichuan University, Chengdu",edu,a0aa32bb7f406693217fba6dcd4aeb6c4d5a479b,citation,https://pdfs.semanticscholar.org/a0aa/32bb7f406693217fba6dcd4aeb6c4d5a479b.pdf,Cascaded Regressor based 3D Face Reconstruction from a Single Arbitrary View Image,2015 -52,COFW,cofw,25.01353105,121.54173736,National Taiwan University of Science and Technology,edu,deb89950939ae9847f0a1a4bb198e6dbfed62778,citation,https://doi.org/10.1109/LSP.2016.2543019,Accurate Facial Landmark Extraction,2016 -53,COFW,cofw,3.12267405,101.65356103,University of Malaya,edu,deb89950939ae9847f0a1a4bb198e6dbfed62778,citation,https://doi.org/10.1109/LSP.2016.2543019,Accurate Facial Landmark Extraction,2016 -54,COFW,cofw,37.4102193,-122.05965487,Carnegie Mellon University,edu,78598e7005f7c96d64cc47ff47e6f13ae52245b8,citation,https://arxiv.org/pdf/1708.00370.pdf,Hand2Face: Automatic synthesis and recognition of hand over face occlusions,2017 -55,COFW,cofw,28.59899755,-81.19712501,University of Central Florida,edu,78598e7005f7c96d64cc47ff47e6f13ae52245b8,citation,https://arxiv.org/pdf/1708.00370.pdf,Hand2Face: Automatic synthesis and recognition of hand over face occlusions,2017 -56,COFW,cofw,52.17638955,0.14308882,University of Cambridge,edu,9901f473aeea177a55e58bac8fd4f1b086e575a4,citation,https://arxiv.org/pdf/1509.04954.pdf,Human and sheep facial landmarks localisation by triplet interpolated features,2016 -57,COFW,cofw,40.00229045,116.32098908,Tsinghua University,edu,e4fa062bff299a0bcef9f6b2e593c85be116c9f1,citation,http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7407641,Cascaded Elastically Progressive Model for Accurate Face Alignment,2017 -58,COFW,cofw,39.9601488,116.35193921,Beijing University of Posts and Telecommunications,edu,5c820e47981d21c9dddde8d2f8020146e600368f,citation,http://pdfs.semanticscholar.org/5c82/0e47981d21c9dddde8d2f8020146e600368f.pdf,Extended Supervised Descent Method for Robust Face Alignment,2014 -59,COFW,cofw,51.49887085,-0.17560797,Imperial College London,edu,29c340c83b3bbef9c43b0c50b4d571d5ed037cbd,citation,https://pdfs.semanticscholar.org/29c3/40c83b3bbef9c43b0c50b4d571d5ed037cbd.pdf,Stacked Dense U-Nets with Dual Transformers for Robust Face Alignment,2018 -60,COFW,cofw,30.19331415,120.11930822,Zhejiang University,edu,5213549200bccec57232fc3ff788ddf1043af7b3,citation,http://doi.acm.org/10.1145/2601097.2601204,Displaced dynamic expression regression for real-time facial tracking and animation,2014 -61,COFW,cofw,51.49887085,-0.17560797,Imperial College London,edu,034b3f3bac663fb814336a69a9fd3514ca0082b9,citation,http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7298991,Unifying holistic and Parts-Based Deformable Model fitting,2015 -62,COFW,cofw,50.74223495,-1.89433739,Bournemouth University,edu,91f0a95b8eb76e8fa24c8267e4a7a17815fc7a11,citation,http://doi.org/10.1007/s41095-016-0068-y,Robust facial landmark detection and tracking across poses and expressions for in-the-wild monocular video,2016 -63,COFW,cofw,45.7413921,126.62552755,Harbin Institute of Technology,edu,91f0a95b8eb76e8fa24c8267e4a7a17815fc7a11,citation,http://doi.org/10.1007/s41095-016-0068-y,Robust facial landmark detection and tracking across poses and expressions for in-the-wild monocular video,2016 -64,COFW,cofw,39.9808333,116.34101249,Beihang University,edu,86b6afc667bb14ff4d69e7a5e8bb2454a6bbd2cd,citation,https://pdfs.semanticscholar.org/86b6/afc667bb14ff4d69e7a5e8bb2454a6bbd2cd.pdf,Attentional Alignment Networks,2018 -65,COFW,cofw,31.20081505,121.42840681,Shanghai Jiao Tong University,edu,86b6afc667bb14ff4d69e7a5e8bb2454a6bbd2cd,citation,https://pdfs.semanticscholar.org/86b6/afc667bb14ff4d69e7a5e8bb2454a6bbd2cd.pdf,Attentional Alignment Networks,2018 -66,COFW,cofw,32.7283683,-97.11201835,University of Texas at Arlington,edu,86b6afc667bb14ff4d69e7a5e8bb2454a6bbd2cd,citation,https://pdfs.semanticscholar.org/86b6/afc667bb14ff4d69e7a5e8bb2454a6bbd2cd.pdf,Attentional Alignment Networks,2018 -67,COFW,cofw,40.0044795,116.370238,Chinese Academy of Sciences,edu,22e2066acfb795ac4db3f97d2ac176d6ca41836c,citation,http://pdfs.semanticscholar.org/26f5/3a1abb47b1f0ea1f213dc7811257775dc6e6.pdf,Coarse-to-Fine Auto-Encoder Networks (CFAN) for Real-Time Face Alignment,2014 -68,COFW,cofw,39.9082804,116.2458527,University of Chinese Academy of Sciences,edu,22e2066acfb795ac4db3f97d2ac176d6ca41836c,citation,http://pdfs.semanticscholar.org/26f5/3a1abb47b1f0ea1f213dc7811257775dc6e6.pdf,Coarse-to-Fine Auto-Encoder Networks (CFAN) for Real-Time Face Alignment,2014 -69,COFW,cofw,43.13800205,-75.22943591,SUNY Polytechnic Institute,edu,69b18d62330711bfd7f01a45f97aaec71e9ea6a5,citation,http://pdfs.semanticscholar.org/69b1/8d62330711bfd7f01a45f97aaec71e9ea6a5.pdf,M-Track: A New Software for Automated Detection of Grooming Trajectories in Mice,2016 -70,COFW,cofw,-30.0338248,-51.218828,Federal University of Rio Grande do Sul,edu,fa08b52dda21ccf71ebc91bc0c4d206ac0aa3719,citation,https://doi.org/10.1109/TIM.2015.2415012,Customized Orthogonal Locality Preserving Projections With Soft-Margin Maximization for Face Recognition,2015 -71,COFW,cofw,-28.234493,-52.38044,University of Passo Fundo,edu,fa08b52dda21ccf71ebc91bc0c4d206ac0aa3719,citation,https://doi.org/10.1109/TIM.2015.2415012,Customized Orthogonal Locality Preserving Projections With Soft-Margin Maximization for Face Recognition,2015 -72,COFW,cofw,34.0224149,-118.28634407,University of Southern California,edu,632b24ddd42fda4aebc5a8af3ec44f7fd3ecdc6c,citation,https://arxiv.org/pdf/1604.02647.pdf,Real-Time Facial Segmentation and Performance Capture from RGB Input,2016 -73,COFW,cofw,22.42031295,114.20788644,Chinese University of Hong Kong,edu,329d58e8fb30f1bf09acb2f556c9c2f3e768b15c,citation,http://openaccess.thecvf.com/content_cvpr_2017_workshops/w33/papers/Wu_Leveraging_Intra_and_CVPR_2017_paper.pdf,Leveraging Intra and Inter-Dataset Variations for Robust Face Alignment,2017 -74,COFW,cofw,40.00229045,116.32098908,Tsinghua University,edu,329d58e8fb30f1bf09acb2f556c9c2f3e768b15c,citation,http://openaccess.thecvf.com/content_cvpr_2017_workshops/w33/papers/Wu_Leveraging_Intra_and_CVPR_2017_paper.pdf,Leveraging Intra and Inter-Dataset Variations for Robust Face Alignment,2017 -75,COFW,cofw,43.07982815,-89.43066425,University of Wisconsin 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University,edu,3d18ce183b5a5b4dcaa1216e30b774ef49eaa46f,citation,https://arxiv.org/pdf/1511.07212.pdf,Face Alignment in Full Pose Range: A 3D Total Solution,2017 -143,COFW,cofw,31.30104395,121.50045497,Fudan University,edu,862d17895fe822f7111e737cbcdd042ba04377e8,citation,http://pdfs.semanticscholar.org/862d/17895fe822f7111e737cbcdd042ba04377e8.pdf,Semi-Latent GAN: Learning to generate and modify facial images from attributes,2017 -144,COFW,cofw,42.718568,-84.47791571,Michigan State University,edu,085ceda1c65caf11762b3452f87660703f914782,citation,http://www.cv-foundation.org/openaccess/content_cvpr_2016/papers/Jourabloo_Large-Pose_Face_Alignment_CVPR_2016_paper.pdf,Large-Pose Face Alignment via CNN-Based Dense 3D Model Fitting,2016 -145,COFW,cofw,39.977217,116.337632,Microsoft Research Asia,company,9aade3d26996ce7ef6d657130464504b8d812534,citation,https://doi.org/10.1109/TNNLS.2016.2618340,Face Alignment With Deep Regression,2018 -146,COFW,cofw,30.5097537,114.4062881,Huazhong University of Science and Technology,edu,9aade3d26996ce7ef6d657130464504b8d812534,citation,https://doi.org/10.1109/TNNLS.2016.2618340,Face Alignment With Deep Regression,2018 -147,COFW,cofw,40.0044795,116.370238,Chinese Academy of Sciences,edu,055cd8173536031e189628c879a2acad6cf2a5d0,citation,https://doi.org/10.1109/BTAS.2017.8272740,Fast multi-view face alignment via multi-task auto-encoders,2017 -148,COFW,cofw,36.20304395,117.05842113,Tianjin University,edu,4223917177405eaa6bdedca061eb28f7b440ed8e,citation,http://pdfs.semanticscholar.org/4223/917177405eaa6bdedca061eb28f7b440ed8e.pdf,B-spline Shape from Motion & Shading: An Automatic Free-form Surface Modeling for Face Reconstruction,2016 -149,COFW,cofw,22.304572,114.17976285,Hong Kong Polytechnic University,edu,4cfa8755fe23a8a0b19909fa4dec54ce6c1bd2f7,citation,https://arxiv.org/pdf/1611.09956v1.pdf,Efficient likelihood Bayesian constrained local model,2017 -150,COFW,cofw,40.0044795,116.370238,Chinese Academy of Sciences,edu,2a4153655ad1169d482e22c468d67f3bc2c49f12,citation,http://www.cv-foundation.org/openaccess/content_cvpr_2016/papers/Zhu_Face_Alignment_Across_CVPR_2016_paper.pdf,Face Alignment Across Large Poses: A 3D Solution,2016 -151,COFW,cofw,42.718568,-84.47791571,Michigan State University,edu,2a4153655ad1169d482e22c468d67f3bc2c49f12,citation,http://www.cv-foundation.org/openaccess/content_cvpr_2016/papers/Zhu_Face_Alignment_Across_CVPR_2016_paper.pdf,Face Alignment Across Large Poses: A 3D Solution,2016 -152,COFW,cofw,40.0044795,116.370238,Chinese Academy of Sciences,edu,090ff8f992dc71a1125636c1adffc0634155b450,citation,http://pdfs.semanticscholar.org/090f/f8f992dc71a1125636c1adffc0634155b450.pdf,Topic-Aware Deep Auto-Encoders (TDA) for Face Alignment,2014 -153,COFW,cofw,51.49887085,-0.17560797,Imperial College London,edu,090ff8f992dc71a1125636c1adffc0634155b450,citation,http://pdfs.semanticscholar.org/090f/f8f992dc71a1125636c1adffc0634155b450.pdf,Topic-Aware Deep Auto-Encoders (TDA) 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not to face: Towards reducing false positive of face detection,2016 -158,COFW,cofw,31.20081505,121.42840681,Shanghai Jiao Tong University,edu,a26fd9df58bb76d6c7a3254820143b3da5bd584b,citation,http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8446759,Monitor Pupils' Attention by Image Super-Resolution and Anomaly Detection,2017 -159,COFW,cofw,51.5247272,-0.03931035,Queen Mary University of London,edu,0f81b0fa8df5bf3fcfa10f20120540342a0c92e5,citation,http://doi.ieeecomputersociety.org/10.1109/CVPR.2015.7299100,"Mirror, mirror on the wall, tell me, is the error small?",2015 -160,COFW,cofw,31.2284923,121.40211389,East China Normal University,edu,83295bce2340cb87901499cff492ae6ff3365475,citation,https://arxiv.org/pdf/1808.01558.pdf,Deep Multi-Center Learning for Face Alignment,2018 -161,COFW,cofw,31.20081505,121.42840681,Shanghai Jiao Tong University,edu,83295bce2340cb87901499cff492ae6ff3365475,citation,https://arxiv.org/pdf/1808.01558.pdf,Deep Multi-Center Learning for Face 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Sciences,edu,a820941eaf03077d68536732a4d5f28d94b5864a,citation,http://www.cv-foundation.org/openaccess/content_iccv_2015/papers/Zhang_Leveraging_Datasets_With_ICCV_2015_paper.pdf,Leveraging Datasets with Varying Annotations for Face Alignment via Deep Regression Network,2015 -191,COFW,cofw,34.0687788,-118.4450094,"University of California, Los Angeles",edu,195d331c958f2da3431f37a344559f9bce09c0f7,citation,http://www.cv-foundation.org/openaccess/content_cvpr_2015/ext/2B_066_ext.pdf,Parsing occluded people by flexible compositions,2015 -192,COFW,cofw,30.5097537,114.4062881,Huazhong University of Science and Technology,edu,5f448ab700528888019542e6fea1d1e0db6c35f2,citation,https://doi.org/10.1109/LSP.2016.2533721,Transferred Deep Convolutional Neural Network Features for Extensive Facial Landmark Localization,2016 -193,COFW,cofw,31.846918,117.29053367,Hefei University of Technology,edu,2f73203fd71b755a9601d00fc202bbbd0a595110,citation,http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8394868,Micro-expression Analysis by Fusing Deep Convolutional Neural Network and Optical Flow,2018 -194,COFW,cofw,33.620813,133.719755,Kochi University of Technology,edu,2f73203fd71b755a9601d00fc202bbbd0a595110,citation,http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8394868,Micro-expression Analysis by Fusing Deep Convolutional Neural Network and Optical Flow,2018 -195,COFW,cofw,32.0565957,118.77408833,Nanjing University,edu,5b0bf1063b694e4b1575bb428edb4f3451d9bf04,citation,http://doi.ieeecomputersociety.org/10.1109/ICCVW.2015.131,Facial Shape Tracking via Spatio-Temporal Cascade Shape Regression,2015 -196,COFW,cofw,31.83907195,117.26420748,University of Science and Technology of China,edu,dd715a98dab34437ad05758b20cc640c2cdc5715,citation,https://doi.org/10.1007/s41095-017-0082-8,Joint head pose and facial landmark regression from depth images,2017 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